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Abstract Stochastic changes in DNA methylation (i.e., spontaneous epimutations) contribute to methylome diversity in plants. Here, we describe AlphaBeta, a computational method for estimating the precise rate of such stochastic events using pedigree-based DNA methylation data as input. We demonstrate how AlphaBeta can be employed to study transgenerationally heritable epimutations in clonal or sexually derived mutation accumulation lines, as well as somatic epimutations in long-lived perennials. Application of our method to published and new data reveals that spontaneous epimutations accumulate neutrally at the genome-wide scale, originate mainly during somatic development and that they can be used as a molecular clock for age-dating trees.

Abstract Background Plants can transmit somatic mutations and epimutations to offspring, which in turn can affect fitness. Knowledge of the rate at which these variations arise is necessary to understand how plant development contributes to local adaption in an ecoevolutionary context, particularly in long-lived perennials. Results Here, we generate a new high-quality reference genome from the oldest branch of a wild Populus trichocarpa tree with two dominant stems which have been evolving independently for 330 years. By sampling multiple, age-estimated branches of this tree, we use a multi-omics approach to quantify age-related somatic changes at the genetic, epigenetic, and transcriptional level. We show that the per-year somatic mutation and epimutation rates are lower than in annuals and that transcriptional variation is mainly independent of age divergence and cytosine methylation. Furthermore, a detailed analysis of the somatic epimutation spectrum indicates that transgenerationally heritable epimutations originate mainly from DNA methylation maintenance errors during mitotic rather than during meiotic cell divisions. Conclusion Taken together, our study provides unprecedented insights into the origin of nucleotide and functional variation in a long-lived perennial plant.

Abstract Background Whole-Genome Bisulfite Sequencing (WGBS) is a Next Generation Sequencing (NGS) technique for measuring DNA methylation at base resolution. Continuing drops in sequencing costs are beginning to enable high-throughput surveys of DNA methylation in large samples of individuals and/or single cells. These surveys can easily generate hundreds or even thousands of WGBS datasets in a single study. The efficient pre-processing of these large amounts of data poses major computational challenges and creates unnecessary bottlenecks for downstream analysis and biological interpretation. Results To offer an efficient analysis solution, we present MethylStar, a fast, stable and flexible pre-processing pipeline for WGBS data. MethylStar integrates well-established tools for read trimming, alignment and methylation state calling in a highly parallelized environment, manages computational resources and performs automatic error detection. MethylStar offers easy installation through a dockerized container with all preloaded dependencies and also features a user-friendly interface designed for experts/non-experts. Application of MethylStar to WGBS from Human, Maize and A. thaliana shows favorable performance in terms of speed and memory requirements compared with existing pipelines. Conclusions MethylStar is a fast, stable and flexible pipeline for high-throughput pre-processing of bulk or single-cell WGBS data. Its easy installation and user-friendly interface should make it a useful resource for the wider epigenomics community. MethylStar is distributed under GPL-3.0 license and source code is publicly available for download from github https://github.com/jlab-code/MethylStar . Installation through a docker image is available from http://jlabdata.org/methylstar.tar.gz

In many plant species, a subset of transcribed genes are characterized by strictly CG-context DNA methylation, referred to as gene body methylation (gbM). The mechanisms that establish gbM are unclear, yet flowering plant species naturally without gbM lack the DNA methyltransferase, CMT3, which maintains CHG (H = A, C, or T) and not CG methylation at constitutive heterochromatin. Here, we identify the mechanistic basis for gbM establishment by expressing CMT3 in a species naturally lacking CMT3. CMT3 expression reconstituted gbM through a progression of de novo CHG methylation on expressed genes, followed by the accumulation of CG methylation that could be inherited even following loss of the CMT3 transgene. Thus, gbM likely originates from the simultaneous targeting of loci by pathways that promote euchromatin and heterochromatin, which primes genes for the formation of stably inherited epimutations in the form of CG DNA methylation.